Embodiments of the present invention generally relate to methods of rapid distinction between debris and growing cells. More specifically, certain embodiments relate to methods of rapid distinction between debris and growing cells in a specimen being imaged by e-Petri systems.
The miniaturization of biomedical imaging tools has the potential to change vastly methods of medical diagnoses and scientific research. More specifically, compact, low-cost microscopes could significantly extend affordable healthcare diagnostics and provide a means for examining and automatically characterizing a large number of cells, as discussed in Psaltis, D., et al., “Developing optofluidic technology through the fusion of microfluidics and optics,” Nature, Vol. 442, pp. 381-386 (2006), which is hereby incorporated by reference in its entirety for all purposes. For example, miniaturized imaging systems may provide a useful alternative to large microscopes in biology labs, allowing for parallel imaging of large number of samples. Some examples of compact microscopes can be found in Cui, X., et al., “Lensless high-resolution on-chip optofluidic microscopes for Caenorhabditis elegans and cell imaging,” Proceedings of the National Academy of Sciences, 105(31), p. 10670 (2008), Seo, S., et al., “Lensfree holographic imaging for on-chip cytometry and diagnostics,” Lab on a Chip, 2009. 9(6), pp. 777-787, Breslauer, D., et al., “Mobile phone based clinical microscopy for global health applications,” (2009), Zheng, G., et al., “Sub-pixel resolving optofluidic microscope for on-chip cell imaging,” Lab on a Chip, 2010. 10(22), pp. 3125-3129, which are hereby incorporated by reference in their entirety for all purposes. Conventional optical microscopes have bulky optics, and have proven to be expensive and difficult to miniaturize.
Rapid advances and commercialization efforts in complementary metal oxide semiconductor (CMOS) imaging sensor technology has led to broad availability of cheap, high-pixel-density imaging sensor chips. In the past few years, these imaging sensor chips enabled the development of new microscopy implementations that are significantly more compact and less expensive than conventional microscopy designs with bulky optics. The optofluidic microscope and the digital in-line holographic microscope are two examples of these new developments. Some examples of optofluidic microscope technologies can be found in Heng, X., et al., “Optofluidic microscopy-method for implementing a high resolution optical microscope on a chip,” Lab Chip, Vol. 6, pp. 1274-1276, Cui, Xiquan, et al., “Lensless high-resolution on-chip optofluidic microscopes for Caenorhabditis elegans and cell imaging,” Proceedings of the National Academy of Science, Vol. 105, p. 10670 (2008), and Zheng, G., Lee, S A., Yang, S., Yang, C., “Sub-pixel resolving optofluidic microscope for on-chip cell imaging. Lab Chip,” Lab Chip, Vol. 10, pp. 3125-3129 (2010) (“Zheng”), which are hereby incorporated by reference in their entirety for all purposes. Some examples of digital in-line holographic microscopy can be found in Repetto, L., Plano, E., Pontiggia, C., “Lensless digital holographic microscope with light-emitting diode illumination,” Opt. Lett., Vol. 29, pp. 1132-1134 (2004), (“Repetto”), Mudanyali, O., et al., “Compact, light-weight and cost-effective microscope based on lensless incoherent holography for telemedicine applications,” Lab on a Chip, Vol. 10, pp. 1417-1428 (2010) (“Mudanyali”), Xu, W., Jericho, M., Meinertzhagen, I., Kreuzer, H., “Digital in-line holography for biological applications,” Proc Natl Acad Sci USA, Vol. 98, pp. 11301-11305 (2001) (“Xu”), Garcia-Sucerquia, J., et al., “Digital in-line holographic microscopy,” Appl. Opt., Vol. 45, pp. 836-850 (2006) (“Garcia-Sucerquia”), Malek M., Allano, D., Coëtmellec, S., Lebrun, D., “Digital in-line holography: Influence of the shadow density on particle field extraction,” Opt. Express, Vol. 12, pp. 2270-2279 (2004) (“Malek”), Isikman, S. O., et al., “Lens-free optical tomographic microscope with a large imaging volume on a chip,” Proc Natl Acad Sci USA, Vol. 108, pp. 7296-7301 (2011), which are hereby incorporated by reference in their entirety for all purposes.
Both optofluidic and in-line holographic microscopy technologies are designed to operate without lenses and, therefore, circumvent their optical limitations, such as aberrations and chromaticity. Both technologies are suitable for imaging dispersible samples, such as blood, fluid cell cultures, and other suspensions of cells or organisms. However, neither can work well with confluent cell cultures or any sample in which cells are contiguously connected over a sizable length scale.
In the case of an optofluidic microscope device, imaging requires fluidic (e.g., microfluidic) flow of specimens across a scanning area. Adherent, confluent, or contiguously arranged specimens are usually incompatible with imaging in a fluidic mode. In addition, the field of view may be limited by the geometry of the fluid channel.
In digital in-line holographic microscopy, the interference intensity distribution of a target under controlled light illumination is measured and then an image reconstruction algorithm is applied to render microscopy images of the target. Two examples of algorithms can be found in Liu, G., Scott, P., “Phase retrieval and twin-image elimination for in-line Fresnel holograms,” J Opt Soc Am A, Vol. 4, pp. 159-165 (1987) (“Liu”), Fienup, J R., “Reconstruction of an object from the modulus of its Fourier transform,” Opt Lett, Vol. 3, pp. 27-29 (1978) (“Fienup”), Koren, G., Polack, F., Joyeux, D., “Iterative algorithms for twin-image elimination in in-line holography using finite-support constraints, J Opt Soc Am A, Vol. 10, pp. 423-433 (1993), which are hereby incorporated by reference in their entirety for all purposes. The image quality depends critically on the extent of the target, the scattering property and the signal-to-noise ratio (SNR) of the measurement processes, which are described in Mudanyali, and Garcia-Sucerquia, Malek, Fienup, and also in Lai, S., King, B., Neifeld, Mass., “Wave front reconstruction by means of phase-shifting digital in-line holography,” Opt Commun., Vol. 173, pp. 155-160 (2000) (“Lai”), and Rodenburg, J., Hurst, A., Cullis, A., “Transmission microscopy without lenses for objects of unlimited size,” Ultramicroscopy, Vol. 107, pp. 227-231 (2007) (“Rodenburg”), which are hereby incorporated by reference in their entirety for all purposes. The method works well for well-isolated targets, such as diluted blood smear slides. However, such approaches appear to have not been applied to targets that occupy more than 0.1 mm2 in total contiguous area coverage with submicron resolution, as found in Repetto, Madanyali, Xu, Garcia-Sucerquia, and also in Biener, G., et al., “Combined reflection and transmission microscope for telemedicine applications in field settings,” Lab Chip, Vol. 11, pp. 2738-2743 (2011), which is hereby incorporated by reference in its entirety for all purposes.
The reason for this limitation is well-known: the loss of phase information during the intensity recording process. In order to recover the phase information, object support has to be used in the iterative phase recovery algorithm, which involves the light field propagation back and forth between the imaging domain (where the intensity data are applied) and object domain (where a priori object constrains are applied), as discussed in Liu. When the test object is real or nonnegative, it is easy to apply the powerful normegativity support constraint to extract the phase information from the recorded diffraction intensity, as discussed in Liu. However, for digital in-line holography, light field in the object domain is complex valued and, therefore, the phase recovery is possible only if the support of the object is sufficiently isolated (i.e., sparsity constrains) or the edges are sharply defined (true boundary), as discussed in Rodenburg and Fienup and also in Denis, L., Lorenz, D., Thiébaut, E., Fournier, C., Trede, D., “Inline hologram reconstruction with sparsity constraints,” Opt Lett, Vol. 34, pp. 3475-3477 (2009), Zhang, F., Pedrini, G., Osten, W., “Phase retrieval of arbitrary complex-valued fields through aperture-plane modulation,” Phys Rev A, Vol. 75, p. 043805 (2007), which are hereby incorporated by reference in their entirety for all purposes. Furthermore, the interference nature of the technique implies that coherence-based noise sources, such as speckles and cross-interference, would be present and would need to be addressed, as discussed in Garcia-Sucerquia and Malek, and also in Xu, L., Miao, J., Asundi, A., “Properties of digital holography based on in-line configuration,” Opt Eng, Vol. 39, pp. 3214-3219 (2000), which is hereby incorporated by reference in its entirety for all purposes. Methods for mitigating problems in digital in-line holographic microscopy have been reported in Lai, Rodenburg and Micó, V., García, J., Zalevsky, Z., Javidi, B., “Phase-Shifting Gabor Holographic Microscopy,” J Disp Technol, Vol. 6, pp. 484-489 (2010), which is hereby incorporated by reference in its entirety for all purposes. The generated images based on these mitigating methods have artifacts that may arise from interference, and are identifiably different and of lower quality than images acquired with conventional microscopes due to coherence based noise sources.
Embodiments of the invention are directed to systems that are improvements over conventional optofluidic and in-line holographic systems that use bulky optics.